Senior Data Scientist - Computer Vision

As a Senior Data Scientist specializing in Computer Vision, your role involves designing, developing, and deploying scalable AI solutions. Your primary responsibilities will include: - Designing, developing, and deploying advanced deep learning models for computer vision use cases such as Image Classification, Object Detection, Image Segmentation, and Video Analytics. - Building scalable ML pipelines using tools like Databricks, MLflow, and Delta Lake. - Performing data preprocessing, augmentation, feature engineering, and optimization for large-scale image/video datasets. - Implementing modern computer vision techniques including CNN architectures, Transfer Learning, and Transformer-based Vision Models. - Managing MLOps best practices such as model versioning, CI/CD pipelines, automated deployment, monitoring, and retraining strategies. - Collaborating with cross-functional teams including engineering, product, and business stakeholders. - Optimizing models for performance, scalability, and cost efficiency in Azure cloud environments. - Ensuring adherence to coding standards, documentation, and best practices. In terms of required technical skills, you should have: - Strong programming expertise in Python. - Hands-on experience with deep learning frameworks like TensorFlow, PyTorch, and Keras. - Strong knowledge of computer vision algorithms and architectures. - Experience with Databricks Notebooks, MLflow, and Delta Lake. - Solid understanding of MLOps frameworks and deployment workflows. - Experience handling large-scale image and video datasets. - Familiarity with UNIX/Linux environments and command-line automation. Additionally, it would be beneficial if you have: - Exposure to Natural Language Processing (NLP). - Experience with transformer-based multimodal models. - Experience working in enterprise-scale AI implementations. - Knowledge of Git-based workflows and DevOps practices. On the soft skills front, you should possess: - Robust communication and stakeholder management skills. - Ability to lead technical discussions and mentor junior team members. - Self-driven with a strong sense of ownership and accountability. As a Senior Data Scientist specializing in Computer Vision, your role involves designing, developing, and deploying scalable AI solutions. Your primary responsibilities will include: - Designing, developing, and deploying advanced deep learning models for computer vision use cases such as Image Classification, Object Detection, Image Segmentation, and Video Analytics. - Building scalable ML pipelines using tools like Databricks, MLflow, and Delta Lake. - Performing data preprocessing, augmentation, feature engineering, and optimization for large-scale image/video datasets. - Implementing modern computer vision techniques including CNN architectures, Transfer Learning, and Transformer-based Vision Models. - Managing MLOps best practices such as model versioning, CI/CD pipelines, automated deployment, monitoring, and retraining strategies. - Collaborating with cross-functional teams including engineering, product, and business stakeholders. - Optimizing models for performance, scalability, and cost efficiency in Azure cloud environments. - Ensuring adherence to coding standards, documentation, and best practices. In terms of required technical skills, you should have: - Strong programming expertise in Python. - Hands-on experience with deep learning frameworks like TensorFlow, PyTorch, and Keras. - Strong knowledge of computer vision algorithms and architectures. - Experience with Databricks Notebooks, MLflow, and Delta Lake. - Solid understanding of MLOps frameworks and deployment workflows. - Experience handling large-scale image and video datasets. - Familiarity with UNIX/Linux environments and command-line automation. Additionally, it would be beneficial if you have: - Exposure to Natural Language Processing (NLP). - Experience with transformer-based multimodal models. - Experience working in enterprise-scale AI implementations. - Knowledge of Git-based workflows and DevOps practices. On the soft skills front, you should possess: - Robust communication and stakeholder management skills. - Ability to lead technical discussions and mentor junior team members. - Self-driven with a strong sense of ownership and accountability.